Coherent change detection (CCD) image products can provide valuable information about subtle scene changes between two synthetic aperture radar (SAR) images of a scene captured at different acquisition times. CCD image products are formed from a pair of complex-valued SAR images by firstly performing a fine, sub-pixel registration of the two SAR images to form a stack of co-registered images, and secondly, computing the sample correlation of the product of the normalized first image with the complex-conjugate of the normalized second image. The resulting CCD image product illustrates variations in coherence.
Loss of coherence is often associated with subtle changes between the acquisition times of the two SAR images. In creating a CCD image product, a sample coherence statistic can be computed in local spatial regions with an M×N box-filter. The sample coherence statistic is a biased estimator for low coherence regions. Furthermore, an increase in a coherence-estimator filter width used to compute the sample coherence decreases a bias in the low coherence regions, and can also lower the resolution of the CCD image product. Hence, there is a tradeoff between allowable bias in low-coherence regions and the resolution of the entire CCD image product.